class RunningParameters
  # p1
  @@random_seed = 1
  # p2
  @@pool_size = 4
  # p3
  @@num_of_ensemble_classifier_members = 2
  # p4
  @@metric = "pctCorrect()"
=begin
    when "pctCorrect()"
      return eval.pctCorrect()
    when "weightedAreaUnderROC()"
      return eval.weightedAreaUnderROC()
    when "weightedFalseNegativeRate()"
      return eval.weightedFalseNegativeRate()
    when "weightedFalsePositiveRate()"
      return eval.weightedFalsePositiveRate()
    when "weightedFMeasure()"
      return eval.weightedFMeasure()
    when "weightedPrecision()"
      return eval.weightedPrecision()
    when "weightedRecall()"
      return eval.weightedRecall()
    when "weightedTrueNegativeRate()"
      return eval.weightedTrueNegativeRate()
    when "weightedTruePositiveRate()"
      return eval.weightedTruePositiveRate()
=end
  # p5
  @@data_set = "breast-cancer.arff"
  # p6
  @@current_fold = 1
  # p7
  @@log_slot_to_show = 0
=begin
  slot 0: peer separation
  slot 1: peer convergence
  slot 2: performance with benchmark data sets

=end
  # p8
  @@im = "simple"
=begin
simple
complex_22
complex_1234
=end
  #p9
  @@time_limit = 100 # 1 second
  # p10
  @@prs_initial_seed = 1

  

  # 1
  def self.set_random_seed( random_seed )
    @@random_seed = random_seed
  end

  # 2
  def self.set_pool_size( pool_size )
    @@pool_size = pool_size
  end

  # 3
  def self.set_num_of_ensemble_classifier_members( num_of_ensemble_classifier_members )
    @@num_of_ensemble_classifier_members = num_of_ensemble_classifier_members
  end

  # 4
  def self.set_metric( metric )
    @@metric = metric
  end
  
  # 5
  def self.set_data_set( data_set )
    @@data_set = data_set
  end

  # 6
  def self.set_current_fold( current_fold )
    @@current_fold = current_fold
  end

  #7
  def self.set_log_slot_to_show( log_slot_to_show )
    @@log_slot_to_show = log_slot_to_show
  end

  #8
  def self.set_im( im )
    @@im = im
  end

  #9
  def self.set_time_limit( time_limit )
    @@time_limit = time_limit
  end

  # 10
  def self.set_prs_initial_seed( prs_initial_seed )
    @@prs_initial_seed = prs_initial_seed
  end

  
  
  # 1
  def self.random_seed
    return @@random_seed
  end

  # 2
  def self.pool_size
    return @@pool_size
  end

  # 3
  def self.num_of_ensemble_classifier_members
    return @@num_of_ensemble_classifier_members
  end

  # 4
  def self.metric
    return @@metric
  end

  # 5
  def self.data_set
    return @@data_set
  end

  # 6
  def self.current_fold
    return @@current_fold
  end

  #7
  def self.log_slot_to_show
    return @@log_slot_to_show
  end

  # 8
  def self.im
    return @@im
  end

  # 9
  def self.time_limit
    return @@time_limit
  end

  # 10
  def self.prs_initial_seed
    return @@prs_initial_seed
  end


end

